{
    "cells": [
     {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
       "# Introduction\n",
       "\n",
       "In this notebook, we perform a basic exploratory analysis of the Iris dataset."
      ]
     },
     {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
       "# Imports\n",
       "import numpy as np\n",
       "import matplotlib.pyplot as plt\n",
       "\n",
       "# Load dataset\n",
       "# (Imaginary code to load iris_data, assuming it's in memory already)\n",
       "iris_data = [\n",
       "    [5.1, 3.5, 1.4, 0.2, \"setosa\"],\n",
       "    [7.0, 3.2, 4.7, 1.4, \"versicolor\"],\n",
       "    [6.3, 3.3, 6.0, 2.5, \"virginica\"]\n",
       "]"
      ]
     },
     {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
       "# Simple descriptive stats\n",
       "sepal_lengths = [row[0] for row in iris_data]\n",
       "print(\"Average sepal length:\", np.mean(sepal_lengths))\n",
       "\n",
       "sepal_widths = [row[1] for row in iris_data]\n",
       "print(\"Average sepal width:\", np.mean(sepal_widths))"
      ]
     }
    ],
    "metadata": {
     "language_info": {
      "name": "python"
     }
    },
    "nbformat": 4,
    "nbformat_minor": 2
   }
